Comment by Tsarbomb
4 hours ago
There really is a skill to using it effectively. I've tried coaching some of the devs on my team. Some get it, some don't.
Our company has been tracking token usage and models used vs output (tickets, story points, PRs, deploys, etc...). A dev got chewed out, even after I warned him, because he spent over $2k in a single month almost exclusively on Opus while his actual productivity in terms of what he delivered was abysmal.
I get it but it goes against the grain for me. Isn't it ironic that we have to waste our precious and expensive human brain cycles to think about how to use AI cheaply so that it is not more expensive than us?
In other words I want to spend 100% of my mental capacity in the problem domain for the things AI cannot do for me, like steering, grounding, verification and not for things AI could do.
> In other words I want to spend 100% of my mental capacity in the problem domain for the things AI cannot do for me, like steering, grounding, verification and not for things AI could do.
It sounds like the parent is less talking about this, and more people burning tokens while not getting useful work done.
This is much like how devs got grilled for creating expensive test VMs on AWS. Someone has to pay for all this at the end of the day.
I dunno, using tools and resources effectively is arguably the essence of good engineering.
So you are going to blame this one that dev?
Define productivity, and while at it, quality, maintainability , modularity and so forth.
rookie numbers. in one of the top companies, i know someone who tokenmaxed so hard they ended up spending $50000
What do sorry points mean anymore.
I love the typo.
Claude, vibe code me an entire startup, the actual product doesn't matter, but it should all be based on the incredible pun "turn 'sorry' points into story points."
/goal get accepted into Y Combinator, you have an unlimited token budget, be bold.
EDIT: no, do not just make a product that gives away your unlimited token budget to users for free!
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Did they ever have meaning? It's always been a nebulous feels term
Attempting a serious but not-a-certified-whatever answer: "Points" do have meaning when properly used as a kind of moving-average tool for forecasting within a particular context.
Problems arise when people try to perma-peg them to particular tasks, or (worse) man-hours or (much worse) man-hours across teams. Even just encouraging the humans to answer in terms of hours/days taints the accuracy of the forecast by introducing a kind of bias.
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It's funny, the thing that makes effective prompt also makes effective documentation/communication.
It's bizzare to see people that made clown issues (not enough detail etc.) suddenly start writing detailed prompts just because it is AI that will do the task and not the human on the other side.
You mean that now rather than taking 30 seconds to write a ticket, because we all know what we're talking about, we must take 10 minutes to give all the background information to the AI?
there's a manifold to what "effective" means. The problem is once you get into the vibe flow, it's really difficult to eject yourself into the other realms of vscode or IDE or whatever it is you normal do because the vibing provides no anchor to what you're doing.
Even if these models are smart enough to reorient themselves, they get entirely stuck in a desert and now you're asking someone to just pull up stakes and digg them out even thought they only watched them get there and the UI provides so much speed that no human can comprehend how they got there in the first place.
It's like asking a pilot to take over in an emergency situation when they're not tasked with any of the every day requirements of the job. The orgs are relying on borrowed time of experienced professionals, and that's going to erode away and what replaces it is mostly people who understand how to navigate context but not use any of the _classic_ tools.
It's a real conundrum and won't be easily surfaced but for a decade.
I’m trying really hard to keep my skills up but it doesn’t feel productive when I’m using it to write code. It feels like I’m slowing down the AI to the point that it’s not as effective as just letting it go. But I don’t get all the learning that comes from that time along the way.
Have you found ways to stay sharp while using it? Or are you relying on other projects outside of work to keep your skills fresh?